Interactive 3D Video Streaming With GPU Rendering And AI Scaling
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Solution Overview
Problem
Existing real-time streaming applications require technical expertise to develop and often fail to provide high visual quality with low latency, are costly, and lack scalability, leading to a complex setup process.
Innovation Solution
A high-performance, low-cost streaming solution using a GPU instance to host services without middleware, employing a peer-to-peer communication network with WebRTC API, and an encapsulated 3D streaming engine for interactive 3D streaming, dynamically adjusting sessions based on client input and using AI for scalable video delivery.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If existing real-time streaming applications are used, then streaming functionality is provided, but technical expertise is required for development and setup process becomes complex
Solution Approach 1:
The patent introduces a streaming server as an intermediary component that mediates between the 3D application and client devices. This server handles the complex encoding, decryption, and streaming operations, allowing end users to access 3D applications without needing technical expertise for setup or configuration.
Solution Approach 2:
The patent extracts the complex streaming functionality into a separate server component, isolating the technical complexity from the client-side application. This allows the 3D application to focus on content delivery while the server handles the intricate streaming protocol, encryption, and adaptive bitrate logic.
2Reliability
If existing real-time streaming applications are used, then streaming is provided, but visual quality and latency performance are insufficient
Solution Approach 1:
The patent implements dynamic adaptive streaming where the server continuously monitors network conditions and adjusts the bitrate, resolution, and encoding parameters in real-time. This dynamic adaptation ensures optimal visual quality while maintaining low latency by adjusting the stream to match current network capabilities.
Solution Approach 2:
The patent changes multiple streaming parameters including bitrate, resolution, frame rate, and encoding format based on network conditions and client capabilities. The server dynamically adjusts these parameters to balance visual quality and latency, providing high-quality streaming when bandwidth allows and lower-latency modes when network conditions are poor.
3Adaptability or versatility
If existing real-time streaming applications are used, then streaming functionality is provided, but cost is high and scalability is limited
Solution Approach 1:
The patent creates a universal streaming server that can serve multiple 3D applications and multiple client devices simultaneously through a single infrastructure. The server handles authentication, session management, and streaming for various applications, eliminating the need for separate streaming systems for each application and reducing overall system cost.
Solution Approach 2:
The patent segments the streaming system into modular components: a centralized streaming server, application servers, and client devices. This segmentation allows independent scaling of each component and enables the system to handle varying loads efficiently, improving scalability while maintaining cost-effectiveness through resource sharing.
Data Source
AI summary
Systems and methods for video processing generates 3D streaming data via an API may be provided. A 3D streaming session may be delivered at a client device with low latency and high throughput capacity. Upon verification of the client device, a server may be selected to support an encapsulated 3D streaming engine to initiate the session. A library file may be injected into an executable file of the encapsulated 3D streaming engine to generate a digital representation of an interactive 3D environment. The interactive 3D environment may be rendered, encoded, and streamed to the client device via a GPU. The 3D streaming session may be adjusted via the client device, and sustained until terminated at the client device. A number of virtual compute instances of encapsulated 3D streaming engines provided by the server may be dynamically adjusted based on metrics and machine learning predictions of connected client devices.